Abstract: When a customer or a new comer invests into a stock market, they want to attain higher profits in short period of time. With less amount of knowledge, they have. The process of attaining higher profit gets very difficult. Sometimes this situation often creates more losses to customers rather than profit. Out of all the books offering investing advice to research papers analysing mathematical prediction models, the stock market has always been centre of attraction for public and academic interest. Number of publications propose strategies with good profits, while others demonstrate the random and unpredictable behaviour of share prices. Shared prices arenít really based on how a company works. Itís based on how mass psychology works. Sentiment Analysis is one of the most popular technique which is widely been used in every industry. Extraction of sentiments from userís comments is used in detecting the user view for a particular company. Sentiment Analysis can help in predicting the mood of people which affects the stock prices and thus can help in prediction of actual prices. Stock market prediction is the act of trying to determine the future value or other financial instrument traded on a financial exchange. In this paper, project is overall based upon the myriad data which is going to be mined from various stock related portals, social media, etc. and after fetching the desired data they have been used for the predictions of related results using NB classifier (Naive Bayes classifier).

Keywords: Sentiment Analysis, Stock Market, Public review, Naive Bayes classifier.